부산대학교 도서관

This paper gives an airborne target recognition and detection method based on fuzzy C-mean clustering, which is implemented by analyzing the motion feature parameters through frequency histogram to get the feature distribution values statistically, and then using the Fuzzy C-mean clustering algorithm to cluster the feature distribution values to get the identification results. distances are calculated based on class centers for new sample data, and through the judgment of the distance threshold with the data detection, which can then mine the abnormal samples. The experimental results show that the method has high identification rate, simple detection and ideal effect.